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Graphical interaction models for multivariate time series1
Authors:Rainer Dahlhaus
Affiliation:Universit?t Heidelberg, Institut für Angewandte Mathematik, Im Neuenheimer Feld 294, 69120 Heidelberg, Germany (e-mail: dahlhaus@statlab.uni-heidelberg.de), DE
Abstract:In this paper we extend the concept of graphical models for multivariate data to multivariate time series. We define a partial correlation graph for time series and use the partial spectral coherence between two components given the remaining components to identify the edges of the graph. As an example we consider multivariate autoregressive processes. The method is applied to air pollution data. Received: June 1999
Keywords:: Graphical models   multivariate time series   partial spectral coherence   spectral estimates   multivariate autoregressive processes   air pollution data.
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